Plotting Single Time Series
taylor_30_min
#> # A tibble: 4,032 x 2
#> date value
#> <dttm> <dbl>
#> 1 2000-06-05 00:00:00 22262
#> 2 2000-06-05 00:30:00 21756
#> 3 2000-06-05 01:00:00 22247
#> 4 2000-06-05 01:30:00 22759
#> 5 2000-06-05 02:00:00 22549
#> 6 2000-06-05 02:30:00 22313
#> 7 2000-06-05 03:00:00 22128
#> 8 2000-06-05 03:30:00 21860
#> 9 2000-06-05 04:00:00 21751
#> 10 2000-06-05 04:30:00 21336
#> # … with 4,022 more rows
Plotting Groups
m4_daily %>% group_by(id)
#> # A tibble: 9,743 x 3
#> # Groups: id [4]
#> id date value
#> <fct> <date> <dbl>
#> 1 D10 2014-07-03 2076.
#> 2 D10 2014-07-04 2073.
#> 3 D10 2014-07-05 2049.
#> 4 D10 2014-07-06 2049.
#> 5 D10 2014-07-07 2006.
#> 6 D10 2014-07-08 2018.
#> 7 D10 2014-07-09 2019.
#> 8 D10 2014-07-10 2007.
#> 9 D10 2014-07-11 2010
#> 10 D10 2014-07-12 2002.
#> # … with 9,733 more rows
m4_daily %>%
group_by(id) %>%
plot_time_series(date, value,
.facet_ncol = 2, .facet_scales = "free")
Adjusting the Smoother
m4_daily %>%
group_by(id) %>%
plot_time_series(date, value,
.facet_ncol = 2, .facet_scales = "free",
.smooth_period = "2 years", .smooth_message = TRUE)
#> trend = 337 days
#> trend = 730 days
#> trend = 338 days
#> trend = 730 days